As is true with most companies, utility companies are striving to reduce overhead costs, while providing more convenience to customers. For example, electric companies are migrating from costly and time-consuming manual methods of determining the amount of power consumed by customers of the power company. Traditionally, a person periodically came to the customer's home, and requested entry to read the consumer power usage from a power meter. This type of process was costly, slow, and intrusive to their customers.
Newer systems provide some level of remote communication between an endpoint such as an electrical meter and a central location. One such system is an automated meter reading (AMR) system that utilizes a power line to establish a data link between a concentrator and endpoint meter reading units positioned downstream from the substation. The concentrator typically includes a transmitter for transmitting control information to the endpoint and a receiver for receiving data such as watt-hour information from the endpoint. The endpoint includes a transmitter, a receiver, and electronics or other circuitry for reading the meter. Other remote meter reading and data communication systems that use modems, radio frequency signals, or PLC signals can communicate with only one endpoint at a time and thus have limited capacity.
These current systems have shortcomings. For example, the capacity of such systems is limited because the concentrator (or other central processing system if modems or RF are used) can receive signals from only one endpoint at a given time. This limitation provides a bottleneck that limits the processing power and flexibility of the system. Additionally, it limits the number of endpoints that the concentrator can communicate within a 24-hour period and hence limits the number of endpoints that can be connected downstream from any given concentrator.
The systems also have little scalability. This limitation is caused by two factors including the limited number of endpoints that can be connected downstream from a concentrator and by the manual programming required every time that an endpoint is added to the system.
Other shortcomings of current AMR and other power line data communication systems relate to reliability, flexibility, and scalability. For example, the system needs to be manually programmed each time an endpoint is added. In another example, if there is a power outage, automated meter reading systems generally require polling of the endpoints to determine which ones are still operational. This polling is slow and consumes processing and communication resources. Furthermore, current systems generally do not have the capability of reestablishing communication between an endpoint and an alternative concentrator if the communication link between the concentrator and the endpoint is disconnected by intentionally taking the substation off line, through a power failure.